Honestly it's not surprising that AI provided answers that were flagged less often as "pedagogically harmful" if we take in account that somehow LLMs create an "average" of all knowledge they ingested.
I think the battle linux vs windows showcases how, in the long run, free software tends to win. In 50+ years, windows will be a footnote in the history of technology, in 100+ years, linux will still be going strong as a multi-generational human endeavor started by a young nerd in the early 90's.
I don't agree with this. Addictive, unless we're talking about a chemical substance or something like that, is a subjective thing. At some point, books, movies, comics, etc, etc might have been considered addictive.
Social networks in general should be banned for underage people, that's the thing. And the social network itself should be liable for verifying the age its users, like a nightclub is liable for people who enter it. No bullshit operating system age verification, that's, trust me, totally intended to protect kids and not to spy on you.
> Addictive, unless we're talking about a chemical substance or something like that, is a subjective thing.
What makes you say that? It's well known that the addictive patterns in these apps trigger dopamine the same way drugs do. In a sense, dopamine is the "chemical substance" central to the addiction. Heroine and algorithms are just different ways to get it.
Everything you do “triggers dopamine”. Reading HN triggers dopamine. Eating breakfast triggers dopamine. Dopamine is also important for movement and many other things.
This is a lame reduction of brain chemistry that has been used to push agendas. Dopamine is not equivalent do addiction.
It's well known, but I'm not convinced it's true. Dopamine levels are measurable by blood test, and some drug abuse studies perform that measurement. Why does the literature on social media and dopamine exclusively talk in vague and general terms, rather than pointing to specific studies where researchers measured dopamine before and after 30 minutes of TikTok scrolling?
Addictiveness is measured by ∆FosB gene expression. The 'addictiveness' of a substance or activity is qualified by how much ∆FosB is expressed. It's decidedly not just a completely subjective thing. Books, movies, comics, etc. can all still be measured on this scale. Everything is addictive in some capacity, generally.
Addiction at least is quite straightforward to differentiate from otherwise engaging things by whether it causes significant harmful effects. E.g. per Wikipedia "Addiction is a neuropsychological disorder characterized by a persistent and intense urge to use a drug or engage in a behavior that produces an immediate psychological reward, despite substantial harm and other negative consequences."
Addictive would be then something that (for a substantial portion of population) has a tendency to cause addiction.
I'm curious to check how faster AAA games will hit the market in the next years compared to the pre-LLM era. Or how much of the aging COBOL code base out there will disappear in the next decade.
When concrete things like that start to happen, then I will start to believe in the 10x claim.
I'm not sure those are great examples. Why not just consider normal apps?
I don't think we'll see AAA game velocity change until asset generation progresses quite a bit, not to mention stuff like rigging. Even then, there's still a layer between code and engine where you have to wire everything together which an LLM will struggle with.
Replacing some old COBOL is probably more of a management decision based on appetite for change and politics rather than development speed.
Aren't there some measurable things like github repo creation, PRs, app store additions, etc. that can be correlated to LLM adoption? Didn't Show HN have to get throttled after LLMs arrived?
I think your answer is the reason why. LLM performance is fine when applied to everything they can do.
Take LLM out that safe space and suddenly they are no silver bullet, in fact they are unless.
So of course those making the 10x claim mean in the safe space where LLM can handle all activities required. You can’t have it both ways 10x and difficult and confusing tasks for LLMs.
Right, I get that. I'm just saying it seems wrong to throw up minority examples. Nobody is pumping out AAA games at speed with LLMs, nor is anyone claiming to do so. There will likely always be some areas where LLMs are bad or useless.
How many people are writing crud apps using mainstream languages vs COBOL though? You don't need 100% silver bullet 1-shot everything, just to recognize the signals that for many use cases, there's a significant shift happening. The safe space is expanding and velocity is increasing.
Definitely the safe space is expanding but how fragile and expensive is this expansion?
AI requires a larger amount of fragile resources to work as opposed to an editor, keyboard and a human.
It some sense it’s a bit like the bitcoin revolution that slowed down once transaction times ballooned out. And blockchains didn’t replace databases as expected. Probably for very good reasons: resources required v. results delivered.
I personally agree that AI is great technology for some great new tools. But we still haven’t found its limits: cost v. results. That happened with bitcoins and blockchains is still outstanding for AIs.
The resources are definitely an issue. I'm still sucking from the corporate teat, but my hope is that by the time the frontier race slows down and they tighten the screws too much, the local models will be good enough. It sounds like recent local models are already getting pretty good for normal duties, but honestly, if it all goes away tomorrow, that's fine too. I'll go back to the old ways. I'd miss the informational capabilities more than the coding capabilities, but I'm no stranger to man pages.
As an aside, I still think there's a place for blockchains. They're not a good replacement for a typical database, but I think some of the concepts are useful. The idea of distributed ledgers and smart contracts have a lot of applications IMHO, particularly in government. The traceability of transactions seems like a great fit to enable transparency of government spending. Of course, governments are allergic to that idea for the usual reasons, but it's still a nice idea. Distributed computing is hard, and it's a shame that blockchains were usurped by crypto bro scams. I'm still rooting for the folks who are trying to push distributed technology forward though.
I feel like that’s tied to the hardware the companies are using. All the banks I’ve worked at run z/OS mainframes, can they even deploy modern run of the mill Go/Python/Rust code or is getting off COBOL reliant on hardware changes?
When a company hires for an entry level public facing position, they always mean a young individual with a welcoming smile instead of a bald middle aged man who has been unemployed for two years. That's something that everybody knows and even the most progressive HR department, overtly or tacitly, will try to enforce. Society is full of small hidden prejudices that people don't really see as harmful.
>I am not trying to be snarky; I used to think that intelligence was intrinsically tied to or perhaps identical with language
I learned a long time ago that this wasn’t the case.
I can speak several languages, and many times when I remember something and want to search for it on Google or any other AI engine, I can’t recall which language I originally read it in.
So whatever mechanism the brain uses to store information, it’s certainly language‑agnostic. There are also many moments when you fully grasp a concept but forget the words to describe it, yet the concept itself remains clear in your mind.
It's very hard to think they wouldn't do something harmful to children again if the economic incentives aligned. For corporations it's just so easy to say sorry, and in the worst case they know an irrelevant fine will be placed in order not "to destroy the business".
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